“We re Trying to Find Cool Things in the Forest” – Exploring Children s Curiosity and Creativity in the Outdoors
Bibliographic record
Abstract
Curiosity and creativity are crucial for children's learning and engagement within their worlds. However, research on creative teaching that also addresses children's curiosity is quite limited. In this case study, we adopted visual methods in combination with video-stimulated recall dialogue (VSRD) to explore children’s experiences in a Forest School (FS) program in Southern Ontario. As researchers, we were particularly interested in the nexus of children’s curiosity and creativity in the process of learning. Participating children, aged 6-12 years, wore GoPro cameras to document their lived experiences in the FS. Informed by constructivism, we examined data vignettes, querying the role of curiosity and creativity within children’s entanglements in the natural environment. The results indicate that open-ended materials within nature invited and sustained curiosity and creativity. Children tended to gravitate to the complexity and ambiguity offered within the natural environment. The research findings have implications for educators, namely the importance of the choice of materials and approaches to support and prioritize children’s curiosity and creativity in learning processes. Implications for inviting educators to capitalize upon inquiry moments and the unknown were also evident.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".